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Seamline optimisation for urban aerial ortho‐image mosaicking using graph cuts / Yunsheng Zhang in Photogrammetric record, vol 33 n° 161 (March 2018)
[article]
Titre : Seamline optimisation for urban aerial ortho‐image mosaicking using graph cuts Type de document : Article/Communication Auteurs : Yunsheng Zhang, Auteur ; Minglei Zhang, Auteur ; Shouji Du, Auteur ; Zhengrong Zou, Auteur ; Chong Fan, Auteur Année de publication : 2018 Article en page(s) : pp 131 - 147 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Orthophotographie, orthoimage
[Termes IGN] algorithme Graph-Cut
[Termes IGN] optimisation (mathématiques)
[Termes IGN] orthophotoplan numérique
[Termes IGN] raccord d'images
[Termes IGN] zone urbaineRésumé : (Auteur) Optimal seamline detection is a key step when composing digital orthophotomaps (DOM) of extensive areas from overlapping ortho‐images. To avoid seamlines passing through buildings when mosaicking, seamline detection between adjacent ortho‐images is casted as a graph‐cut problem. To avoid buildings, colour differences and gradient magnitude derived from the ortho‐images, together with approximate object heights derived from a digital surface model (DSM), are combined for constructing the cost term of the graph. To efficiently obtain an approximate height value for each DOM unit, an expanded normalised DSM is proposed. Furthermore, the designed cost term for final composite ortho‐image merging is weighted to prioritise pixels closest to the nadir point. Experiments with strips of aerial images show that the proposed method obtains seamless mosaicking of ortho‐images without manual work. Numéro de notice : A2018-222 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12232 Date de publication en ligne : 25/03/2018 En ligne : https://doi.org/10.1111/phor.12232 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90042
in Photogrammetric record > vol 33 n° 161 (March 2018) . - pp 131 - 147[article]Extraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos / Yu Feng in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)
[article]
Titre : Extraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos Type de document : Article/Communication Auteurs : Yu Feng, Auteur ; Monika Sester, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] apprentissage profond
[Termes IGN] Berlin
[Termes IGN] cartographie des risques
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] inondation
[Termes IGN] Londres
[Termes IGN] Paris (75)
[Termes IGN] protection civile
[Termes IGN] risque naturel
[Termes IGN] zone sinistrée
[Termes IGN] zone urbaineRésumé : (Auteur) In recent years, pluvial floods caused by extreme rainfall events have occurred frequently. Especially in urban areas, they lead to serious damages and endanger the citizens’ safety. Therefore, real-time information about such events is desirable. With the increasing popularity of social media platforms, such as Twitter or Instagram, information provided by voluntary users becomes a valuable source for emergency response. Many applications have been built for disaster detection and flood mapping using crowdsourcing. Most of the applications so far have merely used keyword filtering or classical language processing methods to identify disaster relevant documents based on user generated texts. As the reliability of social media information is often under criticism, the precision of information retrieval plays a significant role for further analyses. Thus, in this paper, high quality eyewitnesses of rainfall and flooding events are retrieved from social media by applying deep learning approaches on user generated texts and photos. Subsequently, events are detected through spatiotemporal clustering and visualized together with these high quality eyewitnesses in a web map application. Analyses and case studies are conducted during flooding events in Paris, London and Berlin. Numéro de notice : A2018-105 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7020039 En ligne : https://doi.org/10.3390/ijgi7020039 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89530
in ISPRS International journal of geo-information > vol 7 n° 2 (February 2018)[article]Assessing forest windthrow damage using single-date, post-event airborne laser scanning data / Gherardo Chirici in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)
[article]
Titre : Assessing forest windthrow damage using single-date, post-event airborne laser scanning data Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Francesca Bottalico, Auteur ; Francesca Giannetti, Auteur ; Barbara Del Perugia, Auteur ; Davide Travaglini, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 27 - 37 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre urbain
[Termes IGN] dommage matériel
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] peuplement forestier
[Termes IGN] tempête
[Termes IGN] Toscane (Italie)
[Termes IGN] zone urbaineRésumé : (Auteur) One of many possible climate change effects in temperate areas is the increase of frequency and severity of windstorms; thus, fast and cost efficient new methods are needed to evaluate wind-induced damages in forests. We present a method for assessing windstorm damages in forest landscapes based on a two-stage sampling strategy using single-date, post-event airborne laser scanning (ALS) data. ALS data are used for delineating damaged forest stands and for an initial evaluation of the volume of fallen trees. The total volume of fallen trees is then estimated using a two-stage model-assisted approach, where variables from ALS are used as auxiliary information in the difference estimator. In the first stage, a sample of the delineated forest stands is selected, and in the second stage the within-stand damages are estimated by means of line intercept sampling (LIS). The proposed method produces maps of windthrown areas, estimates of forest damages in terms of the total volume of fallen trees, and the uncertainty of the estimates. A case study is presented for a large windstorm that struck the Tuscany Region of Italy the night of the 4th and the 5th of March 2015 and caused extensive damages to trees in both forest and urban areas. The pure field-based estimates from LIS and the ALS-based estimates of stand-level fallen wood were very similar. Our positive results demonstrate the utility of the single-date approach for a fast assessment of windthrow damages in forest stands which is especially useful when pre-event ALS data are not available. Numéro de notice : A2018-630 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx029 Date de publication en ligne : 06/07/2017 En ligne : https://doi.org/10.1093/forestry/cpx029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93215
in Forestry, an international journal of forest research > vol 91 n° 1 (January 2018) . - pp 27 - 37[article]Detection and area estimation for photovoltaic panels in urban hyperspectral remote sensing data by an original NMF-based unmixing method / Moussa Sofiane Karoui (2018)
Titre : Detection and area estimation for photovoltaic panels in urban hyperspectral remote sensing data by an original NMF-based unmixing method Type de document : Article/Communication Auteurs : Moussa Sofiane Karoui, Auteur ; Fatima Zohra Benhalouche, Auteur ; Yannick Deville, Auteur ; Khelifa Djerriri, Auteur ; Xavier Briottet , Auteur ; Arnaud Le Bris , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2018 Projets : HYEP / Weber, Christiane Conférence : IGARSS 2018, IEEE International Geoscience And Remote Sensing Symposium, observing, understanding and forecasting the dynamics of our planet 22/07/2018 27/07/2018 Valencia Espagne Proceedings IEEE Importance : pp 1640 - 1643 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] détection de contours
[Termes IGN] factorisation de matrice non-négative
[Termes IGN] image hyperspectrale
[Termes IGN] panneau photovoltaïque
[Termes IGN] zone urbaineRésumé : (auteur) Hyperspectral remote sensing data offer unique opportunities for the characterization of land surface in urban areas. However, no hyperspectral-unmixing based studies have been conducted to automatically detect photovoltaic panels, which represent one of the important components of energy systems in such areas. In this paper, a hyperspectral-unmixing based method is proposed to detect photovoltaic panels and to estimate their areas. This approach is based on an original multiplicative nonnegative matrix factorization (NMF) algorithm with some known photovoltaic panel spectra. The proposed method can be considered as a partial/informed NMF approach. Experiments are conducted on realistic synthetic and real data to evaluate the performance of the proposed approach. In both cases, obtained results show that the proposed method yields much better overall performance than a method from the literature. Numéro de notice : C2018-047 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2018.8518204 Date de publication en ligne : 05/11/2018 En ligne : https://doi.org/10.1109/IGARSS.2018.8518204 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91270 Exploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region / Tao Zhou in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)
[article]
Titre : Exploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region Type de document : Article/Communication Auteurs : Tao Zhou, Auteur ; Meifang Zhao, Auteur ; Chuanliang Sun, Auteur ; Jianjun Pan, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image GF-1
[Termes IGN] image Sentinel-SAR
[Termes IGN] Kiangsou (Chine)
[Termes IGN] surface imperméable
[Termes IGN] variation saisonnière
[Termes IGN] zone urbaineRésumé : (Auteur) The objective of this research was to investigate the impact of seasonality on urban land-cover mapping and to explore better classification accuracy by using multi-season Sentinel-1A and GF-1 wide field view (WFV) images, and the combinations of both types of images in subtropical monsoon-climate regions in Southeast China. We obtained multi-season Sentinel-1A and GF-1 WFV images, as well as the combinations of both data, by using a support vector machine (SVM) and a random forest (RF) classifier. The backscatter intensity, texture, and interference-coherence images were extracted from Sentinel-1A images, and different combinations of these Sentinel-1A-derived images were used to evaluate their ability to map urban land cover. The results showed that the performance of winter images was better than that of any other season, while the summer images performed the worst. Higher classification accuracy was achieved by using multi-season images, and satisfactory classification results were obtained when using Sentinel-1A images from only three seasons. The best classification result was achieved using a combination of all Sentinel-1A data from all four seasons and GF-1 WFV data from winter, with an overall accuracy of up to 96.02% and a kappa coefficient reaching 0.9502. The performance of textures was slightly better than that of the backscatter-intensity images. Although the coherence data performed the worst, it was still able to distinguish urban impervious surfaces well. In addition, the overall classification accuracy of RF was better than that of SVM. Numéro de notice : A2018-040 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7010003 En ligne : https://doi.org/10.3390/ijgi7010003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89262
in ISPRS International journal of geo-information > vol 7 n° 1 (January 2018)[article]Exploring the relationship between density and completeness of urban building data in OpenStreetMap for quality estimation / Qi Zhou in International journal of geographical information science IJGIS, vol 32 n° 1-2 (January - February 2018)PermalinkFusion tardive d’images SPOT-6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl (2018)PermalinkLocalisation d'objets urbains à partir de sources multiples dont des images aériennes / Lionel Pibre (2018)PermalinkLocalisation par l'image en milieu urbain : application à la réalité augmentée / Antoine Fond (2018)PermalinkOn the production of semantic and textured 3D meshes of large scale urban environments from mobile mapping images and LIDAR scans / Mohamed Boussaha (2018)PermalinkPermalinkA temperature and vegetation adjusted NTL urban index for urban area mapping and analysis / Xiya Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)PermalinkTraitement et analyse des contraintes urbaines pour une optimisation morphologique : Etude comparative des modèles MorVer et SimPLU3D / Alia Belkaid (2018)PermalinkVers une nouvelle approche pour calculer les indicateurs de la densité urbaine via l'imagerie de satellite Alsat-2A / Tarek Medjadj in Bulletin des sciences géographiques, n° 31 (2017 - 2018)PermalinkDouble projection planes method for generating enriched disparity maps from multi-view stereo satellite images / Suliman Alaeldin in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 11 (November 2017)Permalink